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Facial expressions significantly impact identity recognition. Even with constant lighting, varying expressions in real-world images increase identity confusion, showing expression is crucial for face perception.

Keywords:
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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Computer Vision

Background:

  • Facial identity recognition is complex, involving both stable and changeable features.
  • Previous research often used controlled stimuli, limiting real-world applicability.

Purpose of the Study:

  • To investigate how facial expressions influence identity recognition in real-world images.
  • To determine if expression variability causes identity confusion.

Main Methods:

  • Utilized movie segments of two unknown actors to create image pairs with constant lighting but differing expressions.
  • Participants sorted neutral and expressive face image packs into identity piles.
  • Analyzed the distribution of identities within sorted piles.

Main Results:

  • Participants perceived more identities than the actual number, consistent with prior studies.
  • Expressive faces led to significantly more mixed-identity piles compared to neutral faces.
  • Expression variability was identified as a key factor in causing identity confusion.

Conclusions:

  • Facial expression is not disregarded in identity classification; it actively influences recognition.
  • The findings support a dual-process model of face perception, integrating invariant and changeable facial information.
  • Real-world facial image analysis must account for the dynamic nature of expressions.